Abstract

In recent decades, many megacities in the world have suffered from increasingly frequent heat waves. During heat waves, air-conditioners, refrigerators, and electric fans add a considerable peak demand on electrical utility grids, and on the supply side, high temperatures exert adverse effects on electricity generation, transmission, and distribution. Without pro-active planning and mitigation measures, the overloading would result in more frequent blackouts (the complete failure of electricity distribution) and brownouts (voltage reductions). To facilitate a pro-active planning, which aims to replace blackouts and brownouts by a rationing regime in selected sectors, this research proposes an integrated modeling tool which couples a regression model between daily electricity use and maximum temperature over the summer and a mixed input–output model with supply constraints. With the help of available data in Shanghai, China, we show that this tool is capable of quantitatively estimating the overall economic effects and sequential changes in carbon emissions, which a given magnitude of power rationing in a specific sector can exert across all sectors. The availability of such information would enable decision makers to plan an electricity rationing regime at the sector level to meet the double criterions of minimizing the overall economic losses and maximizing the extent of carbon emission reduction.